code: def _log_ndtr_lower(x, series_order):
      """Asymptotic expansion version of `Log[cdf(x)]`, appropriate for `x<<-1`."""
      x_2 = tf.square(x)
      # Log of the term multiplying (1 + sum)
      log_scale = (
          -0.5 * x_2
          - tf.math.log(-x)
          - tf.constant(0.5 * np.log(2.0 * np.pi), dtype=x.dtype)
      )
      return log_scale + tf.math.log(
          _log_ndtr_asymptotic_series(x, series_order)
      )
  
file_path: probability/tensorflow_probability/python/internal/special_math.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
label_desc: Use image node_id 4 for calling a global function with example usage: _log_ndtr_lower(x, series_order) and returns: unknown